Exactly. Radar gives you direct range data; camera pixels need to be processed by ML to infer range data, and the latter is never going to be as close to ground truth as the former, so the former should be prioritized.

Not quite. Light waves are so short you'll get some return from almost any surface. This isn't true of radar, and it's not just what substance the outbound radar hits but how flat it is, too. You may get no return. Or almost none. Even round posts give very little return IIRC. There's also an echo problem with long waves such as sound and radar, particularly in urban areas. In which case what you think is a firm direct return may be a very indirect return that happens to be in synch with the signal you were expecting.

Its interesting, that kind of object level fusion is a fairly different problem to training visual perception, following some of the less in fashion robotics techniques. I wonder if its a case of the Tesla engineers focusing on the fad technologies (or just their strengths) more than its a hardware cost thing.